Journal of Pathology Informatics Journal of Pathology Informatics
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RESEARCH ARTICLE
Year : 2019  |  Volume : 10  |  Issue : 1  |  Page : 26

Development of a calculated panel reactive antibody web service with local frequencies for platelet transfusion refractoriness risk stratification


1 Department of Medicine, Division of General Internal Medicine and Primary Care, Brigham and Women's Hospital; Department of Medicine, Division of General Internal Medicine, Massachusetts General Hospital; Harvard Medical School, Boston; Partners HealthCare, Somerville, MA, USA
2 Partners HealthCare, Somerville, MA, USA
3 Department of Pathology, Brigham and Women's Hospital, Boston, MA, USA
4 Harvard Medical School; Department of Pathology, Brigham and Women's Hospital, Boston, MA, USA
5 Harvard Medical School; Department of Medicine, Division of Renal Medicine, Brigham and Women's Hospital, Boston, MA, USA

Correspondence Address:
Dr. William J Gordon
Division of General Internal Medicine and Primary Care, Brigham and Women's Hospital, 1620 Tremont Street, Boston, MA 02115
USA
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/jpi.jpi_29_19

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Background: Calculated panel reactive antibody (cPRA) scoring is used to assess whether platelet refractoriness is mediated by human leukocyte antigen (HLA) antibodies in the recipient. cPRA testing uses a national sample of US kidney donors to estimate the population frequency of HLA antigens, which may be different than HLA frequencies within local platelet inventories. We aimed to determine the impact on patient cPRA scores of using HLA frequencies derived from typing local platelet donations rather than national HLA frequencies. Methods: We built an open-source web service to calculate cPRA scores based on national frequencies or custom-derived frequencies. We calculated cPRA scores for every hematopoietic stem cell transplantation (HSCT) patient at our institution based on the United Network for Organ Sharing (UNOS) frequencies and local frequencies. We compared frequencies and correlations between the calculators, segmented by gender. Finally, we put all scores into three buckets (mild, moderate, and high sensitizations) and looked at intergroup movement. Results: 2531 patients that underwent HSCT at our institution had at least 1 antibody and were included in the analysis. Overall, the difference in medians between each group's UNOS cPRA and local cPRA was statistically significant, but highly correlated (UNOS vs. local total: 0.249 and 0.243, ρ = 0.994; UNOS vs. local female: 0.474 and 0.463, ρ = 0.987, UNOS vs. local male: 0.165 and 0.141, ρ = 0.996;P< 0.001 for all comparisons). The median difference between UNOS and cPRA scores for all patients was low (male: 0.014, interquartile range [IQR]: 0.004–0.029; female: 0.0013, IQR: 0.003–0.028). Placement of patients into three groups revealed little intergroup movement, with 2.96% (75/2531) of patients differentially classified. Conclusions: cPRA scores using local frequencies were modestly but significantly different than those obtained using national HLA frequencies. We released our software as open source, so other groups can calculate cPRA scores from national or custom-derived frequencies. Further investigation is needed to determine whether a local-HLA frequency approach can improve outcomes in patients who are immune-refractory to platelets.


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